ArticleThe annals of applied statistics2017
BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES.
Article in The annals of applied statistics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 5 citations in OpenAlex.
- Comparison of Ensemble Techniques for Early Prediction of Alzhiemer Disease.Research square · 2024Article
- A Bayesian semi-parametric model for learning biomarker trajectories and changepoints in the preclinical phase of Alzheimer's disease.Biometrics · 2024Article
- Entorhinal and Transentorhinal Atrophy in Preclinical Alzheimer's Disease.Frontiers in neuroscience · 2020Article
- Identifying Changepoints in Biomarkers During the Preclinical Phase of Alzheimer's Disease.Frontiers in aging neuroscience · 2019Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
We consider in this paper a statistical two-phase regression model in which the change point of a disease biomarker is measured relative to another point in time, such as the manifestation of the disease, which is subject to right-censoring (i.e., possibly unobserved over the entire course of the study). We develop point estimation methods for this model, based on maximum likelihood, and bootstrap validation methods. The effectiveness of our approach is illustrated by numerical simulations, and by the estimation of a change point for amygdalar atrophy in the context of Alzheimer's disease, wherein it is related to the cognitive manifestation of the disease.
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